Find a \(QR\) factorization of the matrix in Exercise 11.

Short Answer

Expert verified

The factorization of the matrix is,\(A = \left( {\begin{aligned}{{}{r}}{\frac{1}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{1}{2}}\\{\frac{{ - 1}}{{\sqrt 5 }}}&0&0\\{\frac{{ - 1}}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{1}{2}}\\{\frac{1}{{\sqrt 5 }}}&{\frac{{ - 1}}{2}}&{\frac{1}{2}}\\{\frac{1}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{{ - 1}}{2}}\end{aligned}} \right)\left( {\begin{aligned}{{}{}}{\sqrt 5 }&{ - \sqrt 5 }&{4\sqrt 5 }\\0&6&{ - 2}\\0&0&4\end{aligned}} \right)\).

Step by step solution

01

\(QR\) factorization of a Matrix

A matrix with order \(m \times n\) can be written as the multiplication of an upper triangularmatrix \(R\) and a matrix \(Q\) which is formed by applying Gram–Schmidt orthogonalizationprocess to the \({\rm{col}}\left( A \right)\).

The matrix \(R\) can be found by the formula \({Q^T}A = R\).

02

Finding the matrix \(R\)

From exercise 11 we have,

\(A = \left( {\begin{aligned}{{}{r}}1&2&5\\{ - 1}&1&{ - 4}\\{ - 1}&4&{ - 3}\\1&{ - 4}&7\\1&2&1\end{aligned}} \right)\)

Again, with help of exercise 11 where we have calculated the orthogonal basisfor columnsof \(A\) we have,

\(\left\{ {\left( {\begin{aligned}{{}{r}}1\\{ - 1}\\{ - 1}\\1\\1\end{aligned}} \right),\left( {\begin{aligned}{{}{r}}3\\0\\3\\{ - 3}\\3\end{aligned}} \right),\left( {\begin{aligned}{{}{r}}2\\0\\2\\2\\{ - 2}\end{aligned}} \right)} \right\}\)

Now normalizing them we get

\(\begin{aligned}{}\left\{ {\frac{{{v_1}}}{{\left\| {{v_1}} \right\|}},\frac{{{v_2}}}{{\left\| {{v_2}} \right\|}},\frac{{{v_3}}}{{\left\| {{v_3}} \right\|}}} \right\} & = \left\{ {\frac{{\left( {\begin{aligned}{{}{r}}1\\{ - 1}\\{ - 1}\\1\\1\end{aligned}} \right)}}{{\sqrt 5 }},\frac{{\left( {\begin{aligned}{{}{r}}3\\0\\3\\{ - 3}\\3\end{aligned}} \right)}}{{\sqrt {4 \cdot 9} }},\frac{{\left( {\begin{aligned}{{}{r}}2\\0\\2\\2\\{ - 2}\end{aligned}} \right)}}{{\sqrt {16} }}} \right\}\\\left\{ {\frac{{{v_1}}}{{\left\| {{v_1}} \right\|}},\frac{{{v_2}}}{{\left\| {{v_2}} \right\|}},\frac{{{v_3}}}{{\left\| {{v_3}} \right\|}}} \right\} & = \left\{ {\left( {\begin{aligned}{{}{r}}{\frac{1}{{\sqrt 5 }}}\\{\frac{{ - 1}}{{\sqrt 5 }}}\\{\frac{{ - 1}}{{\sqrt 5 }}}\\{\frac{1}{{\sqrt 5 }}}\\{\frac{1}{{\sqrt 5 }}}\end{aligned}} \right),\left( {\begin{aligned}{{}{r}}{\frac{1}{2}}\\0\\{\frac{1}{2}}\\{ - \frac{1}{2}}\\{\frac{1}{2}}\end{aligned}} \right),\left( {\begin{aligned}{{}{r}}{\frac{1}{2}}\\0\\{\frac{1}{2}}\\{\frac{1}{2}}\\{ - \frac{1}{2}}\end{aligned}} \right)} \right\}\end{aligned}\)

Hence, the matrix \(Q\) will be:

\(Q = \left( {\begin{aligned}{{}{r}}{\frac{1}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{1}{2}}\\{\frac{{ - 1}}{{\sqrt 5 }}}&0&0\\{\frac{{ - 1}}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{1}{2}}\\{\frac{1}{{\sqrt 5 }}}&{\frac{{ - 1}}{2}}&{\frac{1}{2}}\\{\frac{1}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{{ - 1}}{2}}\end{aligned}} \right)\)

Now, calculate \({Q^T}A = R\) by using \(A\) and \(Q\).

\(\begin{aligned}{}R & = {Q^T}A\\ & = \left( {\begin{aligned}{{}{r}}{\frac{1}{{\sqrt 5 }}}&{\frac{1}{{\sqrt 5 }}}&{\frac{1}{{\sqrt 5 }}}&{\frac{1}{{\sqrt 5 }}}&{\frac{1}{{\sqrt 5 }}}\\{\frac{1}{2}}&0&{\frac{1}{2}}&{\frac{{ - 1}}{2}}&{\frac{1}{2}}\\{\frac{1}{2}}&0&{\frac{1}{2}}&{\frac{1}{2}}&{\frac{{ - 1}}{2}}\end{aligned}} \right)\left( {\begin{aligned}{{}{r}}1&2&5\\{ - 1}&1&{ - 4}\\{ - 1}&4&{ - 3}\\1&{ - 4}&7\\1&2&1\end{aligned}} \right)\\ & = \left( {\begin{aligned}{{}{r}}{\sqrt 5 }&{ - \sqrt 5 }&{4\sqrt 5 }\\0&6&{ - 2}\\0&0&4\end{aligned}} \right)\end{aligned}\)

Hence, the required factorization is,\(A = \left( {\begin{aligned}{{}{r}}{\frac{1}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{1}{2}}\\{\frac{{ - 1}}{{\sqrt 5 }}}&0&0\\{\frac{{ - 1}}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{1}{2}}\\{\frac{1}{{\sqrt 5 }}}&{\frac{{ - 1}}{2}}&{\frac{1}{2}}\\{\frac{1}{{\sqrt 5 }}}&{\frac{1}{2}}&{\frac{{ - 1}}{2}}\end{aligned}} \right)\left( {\begin{aligned}{{}{}}{\sqrt 5 }&{ - \sqrt 5 }&{4\sqrt 5 }\\0&6&{ - 2}\\0&0&4\end{aligned}} \right)\).

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Most popular questions from this chapter

In exercises 1-6, determine which sets of vectors are orthogonal.

\(\left[ {\begin{array}{*{20}{c}}5\\{ - 4}\\0\\3\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{ - 4}\\1\\{ - 3}\\8\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}3\\3\\5\\{ - 1}\end{array}} \right]\)

In Exercises 7–10, let\[W\]be the subspace spanned by the\[{\bf{u}}\]’s, and write y as the sum of a vector in\[W\]and a vector orthogonal to\[W\].

10.\[y = \left[ {\begin{aligned}3\\4\\5\\6\end{aligned}} \right]\],\[{{\bf{u}}_1} = \left[ {\begin{aligned}1\\1\\0\\{ - 1}\end{aligned}} \right]\],\[{{\bf{u}}_2} = \left[ {\begin{aligned}1\\0\\1\\1\end{aligned}} \right]\],\[{{\bf{u}}_3} = \left[ {\begin{aligned}0\\{ - 1}\\1\\{ - 1}\end{aligned}} \right]\]

Compute the quantities in Exercises 1-8 using the vectors

\({\mathop{\rm u}\nolimits} = \left( {\begin{aligned}{*{20}{c}}{ - 1}\\2\end{aligned}} \right),{\rm{ }}{\mathop{\rm v}\nolimits} = \left( {\begin{aligned}{*{20}{c}}4\\6\end{aligned}} \right),{\rm{ }}{\mathop{\rm w}\nolimits} = \left( {\begin{aligned}{*{20}{c}}3\\{ - 1}\\{ - 5}\end{aligned}} \right),{\rm{ }}{\mathop{\rm x}\nolimits} = \left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\\3\end{aligned}} \right)\)

  1. \({\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} ,{\rm{ }}{\mathop{\rm v}\nolimits} \cdot {\mathop{\rm u}\nolimits} ,\,\,{\mathop{\rm and}\nolimits} \,\,\frac{{{\mathop{\rm v}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}{{{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm u}\nolimits} }}\)

Compute the least-squares error associated with the least square solution found in Exercise 4.

Compute the quantities in Exercises 1-8 using the vectors

\({\mathop{\rm u}\nolimits} = \left( {\begin{aligned}{*{20}{c}}{ - 1}\\2\end{aligned}} \right),{\rm{ }}{\mathop{\rm v}\nolimits} = \left( {\begin{aligned}{*{20}{c}}4\\6\end{aligned}} \right),{\rm{ }}{\mathop{\rm w}\nolimits} = \left( {\begin{aligned}{*{20}{c}}3\\{ - 1}\\{ - 5}\end{aligned}} \right),{\rm{ }}{\mathop{\rm x}\nolimits} = \left( {\begin{aligned}{*{20}{c}}6\\{ - 2}\\3\end{aligned}} \right)\)

5. \(\left( {\frac{{{\mathop{\rm u}\nolimits} \cdot {\mathop{\rm v}\nolimits} }}{{{\mathop{\rm v}\nolimits} \cdot {\mathop{\rm v}\nolimits} }}} \right){\mathop{\rm v}\nolimits} \)

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